14 citations · 45 across the 13 of their papers we have counts for
9 papers · 1 filter
Information theoretical clustering is hard to approximate
Ferdinando Cicalese, Eduardo Laber
An impurity measures is a function that assigns a -dimensional vector to a non-negative value so that the more homo…
Minimization of Gini impurity via connections with the k-means problem
Eduardo Sany Laber, Lucas Murtinho
The Gini impurity is one of the measures used to select attribute in Decision Trees/Random Forest construction. In this note we discuss connections between the problem of computing…
Approximation Algorithms for Clustering via Weighted Impurity Measures
Ferdinando Cicalese, Eduardo Laber
An impurity measures maps a -dimensional vector to a non-negative value so that the more homogeneous , the larger its impurit…
Searching for a superlinear lower bounds for the Maximum Consecutive Subsums Problem and the (min,+)-convolution
Wilfredo Bardales Roncalla, Eduardo Laber, Ferdinando Cicalese
Given a sequence of n numbers, the Maximum Consecutive Subsums Problem (MCSP) asks for the maximum consecutive sum of lengths l for each l = 1,...,n. No algorithm is known for this…
Trading off Worst and Expected Cost in Decision Tree Problems and a Value Dependent Model
Aline Saettler, Eduardo Laber, Ferdinando Cicalese
We study the problem of evaluating a discrete function by adaptively querying the values of its variables until the values read uniquely determine the value of the function. Readin…
Decision Trees for Function Evaluation - Simultaneous Optimization of Worst and Expected Cost
Ferdinando Cicalese, Eduardo Laber, Aline Medeiros Saettler
In several applications of automatic diagnosis and active learning a central problem is the evaluation of a discrete function by adaptively querying the values of its variables unt…